Paper Type
ERF
Abstract
This study conceptualizes enterprise AI systems as mechanisms of algorithmic knowledge appropriation that transform individual tacit expertise into organizational digital assets. While prior research on AI in organizations emphasizes automation and augmentation, we theorize a distinct process through which AI systems institutionalize cognitive work patterns by capturing interaction traces embedded in digital workflows. We develop a conceptual model explaining how AI-enabled knowledge capture shapes employee perceptions of expertise ownership, triggers strategic behavioral adaptation, and influences organizational capability formation.
Paper Number
1627
Recommended Citation
Andrew-Essien, Anietie, "When AI Learns the Worker: Enterprise AI and the Institutionalization of Expertise" (2026). AMCIS 2026 Proceedings. 9.
https://aisel.aisnet.org/amcis2026/sigcnow/sigcnow/9
When AI Learns the Worker: Enterprise AI and the Institutionalization of Expertise
This study conceptualizes enterprise AI systems as mechanisms of algorithmic knowledge appropriation that transform individual tacit expertise into organizational digital assets. While prior research on AI in organizations emphasizes automation and augmentation, we theorize a distinct process through which AI systems institutionalize cognitive work patterns by capturing interaction traces embedded in digital workflows. We develop a conceptual model explaining how AI-enabled knowledge capture shapes employee perceptions of expertise ownership, triggers strategic behavioral adaptation, and influences organizational capability formation.
Comments
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